This paper reviews the empirical methods used in the accounting literature to draw causal inferences. Recent years have seen a burgeoning growth in the use of methods that seek to exploit as-if random variation in observational settings—i.e., “quasi-experiments.” We provide a synthesis of the major assumptions of these methods, discuss several practical considerations relevant to the application of these methods in the accounting literature, and provide a framework for thinking about whether and when quasi-experimental and non-experimental methods are well-suited for addressing causal questions of interest to accounting researchers. While there is growing interest in addressing causal questions within the literature, we caution against the idea that one should restrict attention to only those causal questions for which there are quasi-experiments. We offer a complementary approach for addressing causal questions that does not rely on the availability of a quasi-experiment, but rather relies on a combination of economic theory, developing and falsifying alternative explanations, triangulating results across multiple settings, measures, and research designs, and caveating results where appropriate.
